Dong Rui, Hu Taojun, Zhang Yunjun, Li Yang, Zhou Xiao-Hua
Yau Mathematical Sciences Center, Tsinghua University, Beijing 100084, China.
Yanqi Lake Beijing Institute of Mathematical Sciences and Applications, Beijing 101408, China.
Vaccines (Basel). 2022 Mar 24;10(4):496. doi: 10.3390/vaccines10040496.
Omicron, the latest SARS-CoV-2 Variant of Concern (VOC), first appeared in Africa in November 2021. At present, the question of whether a new VOC will out-compete the currently predominant variant is important for governments seeking to determine if current surveillance strategies and responses are appropriate and reasonable. Based on both virus genomes and daily-confirmed cases, we compare the additive differences in growth rates and reproductive numbers (R0) between VOCs and their predominant variants through a Bayesian framework and phylo-dynamics analysis. Faced with different variants, we evaluate the effects of current policies and vaccinations against VOCs and predominant variants. The model also predicts the date on which a VOC may become dominant based on simulation and real data in the early stage. The results suggest that the overall additive difference in growth rates of B.1.617.2 and predominant variants was 0.44 (95% confidence interval, 95% CI: -0.38, 1.25) in February 2021, and that the VOC had a relatively high R0. The additive difference in the growth rate of BA.1 in the United Kingdom was 6.82 times the difference between Delta and Alpha, and the model successfully predicted the dominating process of Alpha, Delta and Omicron. Current vaccination strategies remain similarly effective against Delta compared to the previous variants. Our model proposes a reliable Bayesian framework to predict the spread trends of VOCs based on early-stage data, and evaluates the effects of public health policies, which may help us better prepare for the upcoming Omicron variant, which is now spreading at an unprecedented speed.
奥密克戎是最新的严重急性呼吸综合征冠状病毒2(SARS-CoV-2)关注变异株(VOC),于2021年11月首次在非洲出现。目前,对于寻求确定当前监测策略和应对措施是否恰当合理的各国政府而言,一种新的关注变异株是否会胜过当前占主导地位的变异株这一问题至关重要。基于病毒基因组和每日确诊病例,我们通过贝叶斯框架和系统发育动力学分析,比较了关注变异株与其占主导地位的变异株在增长率和繁殖数(R0)方面的累加差异。面对不同的变异株,我们评估了当前针对关注变异株和占主导地位变异株的政策及疫苗接种的效果。该模型还根据早期的模拟和实际数据预测了一种关注变异株可能成为主导的日期。结果表明,2021年2月,B.1.617.2及其占主导地位的变异株在增长率方面的总体累加差异为0.44(95%置信区间,95%CI:-0.38,1.25),且该关注变异株具有相对较高的R0。英国BA.1的增长率累加差异是德尔塔与阿尔法之间差异的6.82倍,该模型成功预测了阿尔法、德尔塔和奥密克戎的主导过程。与之前的变异株相比,当前的疫苗接种策略对德尔塔仍然同样有效。我们的模型提出了一个可靠的贝叶斯框架,以根据早期数据预测关注变异株的传播趋势,并评估公共卫生政策的效果,这可能有助于我们更好地为目前以前所未有的速度传播的奥密克戎变异株做好准备。